A key problem in information retrieval is inferring the searcher's interest in the results, which can be used for implicit feedback, query suggestion, and result ranking and summarization. One important indicator of searcher interest is gaze position -that is, the results or the terms in a result listing where a searcher concentrates her attention. Capturing this information normally requires eye tracking equipment, which until now has limited the use of gaze-based feedback to the laboratory. While previous research has reported a correlation between mouse movement and gaze position, we are not aware of prior work on automatically inferring searcher's gaze position from mouse movement or similar interface interactions. In this paper, we report the first results on automatically inferring whether the searcher's gaze position is coordinated with the mouse position -a crucial step towards predicting the searcher gaze position by analyzing the computer mouse movements.

We propose a simplified parity meter for photonic qubits with cross-Kerr nonlinearities, homodyne measurement, and some optical elements. Our scheme has lower error probability than the protocol proposed in Nemoto and Munro [Phys. Rev. Lett. 93, 250502 (2004)]. Based on the present parity meter, we achieve cluster-state preparation, a complete Bell-state analyzer, and quantum teleportation. All of these schemes are nearly deterministic in the regime with little noise and include less optical elements, which makes our schemes more meaningful for large-scale quantum computing.

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Understanding the intent underlying user queries may help personalize search results and improve user satisfaction. In this paper, we develop a methodology for using ad clickthrough logs, query specific information, and the content of search engine result pages to study characteristics of query intents, specially commercial intent. The findings of our study suggest that ad clickthrough features, query features, and the content of search engine result pages are together effective in detecting query intent. We also study the effect of query type and the number of displayed ads on the average clickthrough rate. As a practical application of our work, we show that modeling query intent can improve the accuracy of predicting ad clickthrough for previously unseen queries.

Clickthrough on search results have been successfully used to infer user interest and preferences, but are often noisy and potentially ambiguous. We explore the potential of a complementary, more sensitive signal -mouse movementsin providing insights into the intent behind a web search query. We report preliminary results of studying user mouse movements on search result pages, with the goal of inferring user intent -in particular, to explore whether we can automatically distinguish the different query classes such as navigational vs. informational. Our preliminary exploration confirms the value of studying mouse movements for user intent inference, and suggests interesting avenues for future exploration.

Inspired by recent work [A. W. Carr and M. Saffman, Phys. Rev. Lett. 111, 033607 (2013)], we propose a simplified scheme to prepare the two-atom maximally entangled states via dissipative Rydberg pumping. Compared with the former scheme, the simplified one involves less classical laser fields and Rydberg interactions, and the asymmetric Rydberg interactions are avoided. Master equation simulations demonstrate that the fidelity and the Clauser-Horne-Shimony-Holt correlation of the maximally entangled state could reach up to 0.999 and 2.821, respectively, under certain conditions. Furthermore, we extend the physical thoughts to prepare the three-dimensional entangled state, the numerical simulations show that, in theory, both the fidelity and the Negativity of the desired entanglement could be very close to unity under certain conditions.

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